Staff AI Solutions Engineer

Role Description

Included Health is seeking a hands-on Staff AI Solutions Engineer to be part of our IT Solutions team. The right candidate will be passionate about the advancements in AI and will have experience in owning deployment/hosting decisions and implementation.

The engineer in this role will design, build, and operate internal automations, AI agents, and secure integrations that increase corporate teams productivity while meeting healthcare security and compliance requirements. This role blends software engineering, systems integration, architecture, and practical LLM expertise to take POCs to production.

The engineer in this role will partner closely with and build internal solutions for Cybersecurity, Compliance, Finance, HR, Product, Engineering, Operations, Clinical teams, and business stakeholders to deliver AI tooling with metrics-backed value across the enterprise. This role will report to the Director, Digital Workplace.

Responsibilities

• Design, build, deploy, and maintain production LLM-based solutions and agent workflows.
• Own the technical strategy and reference architecture for enterprise AI solutions across multiple teams and business functions.
• Lead high-complexity, cross-functional AI initiatives from ambiguous problem definition through production adoption and measurable business outcomes.
• Define and evolve reusable platform capabilities, implementation standards, and governance patterns that enable safe, scalable AI adoption beyond a single team.
• Review citizen developer AI agents/solutions to provide recommendations for optimization, ensure compliance with guidelines, and measure value.
• Influence roadmap and investment decisions across the company through technical leadership and business-value analysis.
• Drive technical debates, align stakeholders on tradeoffs, and unblock multi-team execution for strategically important AI initiatives.
• Implement, review, and validate code produced by models; write production-quality code and run code reviews to ensure correctness and security.
• Build robust integrations and connectors (MCP, REST/GraphQL APIs, webhooks, SDKs, CLIs) between AI tooling and enterprise SaaS (e.g., Okta, Google Workspace, Slack, Jira, Confluence, Jamf).
• Own end-to-end deployment and lifecycle for AI services: CI/CD pipelines, Infrastructure as Code modules (Terraform), cloud deployment (GCP/AWS), monitoring, and incident/runbook playbooks.
• Establish and operate model evaluation, monitoring, and governance: accuracy and safety metrics, hallucination detection, drift monitoring, telemetry, alerting, and human-in-the-loop controls.
• Lead vendor evaluations and POCs across commercial and open-source LLM/agent platforms; produce comparative performance, risk, and TCO recommendations to inform adoption.
• Partner with Cybersecurity and Compliance to design PHI-safe data handling patterns (sanitization, tokenization, least-privilege access, audit logging) and ensure AI solutions align with relevant controls and policies.
• Create and maintain architecture diagrams, API documentation, runbooks, support documentation, and onboarding materials so solutions are maintainable and auditable.
• Mentor engineers and influence architectural standards for AI/LLM adoption across Digital Workplace; contribute reusable libraries and IaC modules to accelerate future builds.
• Drive automation of operational tasks (provisioning, onboarding, common workflows) via agents and workflow tooling to reduce manual processes.
• Partner with Technology Services leadership to implement AI spend management tools and value tracking.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
• 8+ years professional software engineering/systems integration experience.

Requirements

• Practical experience owning the complete lifecycle of LLMs and agents.
• Experience evaluating model performance, mitigating hallucinations and bias, and implementing human-in-the-loop controls.
• Ability to define reference architectures and reusable patterns for AI services used across multiple teams.
• Experience making architectural tradeoffs across reliability, latency, cost, security, and maintainability in production systems.
• Experience establishing engineering standards, guardrails, and paved-road patterns for AI development and deployment.
• Experience optimizing model/runtime cost, usage controls, and value measurement.
• Strong coding experience in Python and/or TypeScript/JavaScript with production software engineering discipline (code reviews, testing, CI/CD).
• Experience designing and building API integrations (REST/GraphQL), webhooks, and custom connectors to SaaS applications.
• Experience with Infrastructure as Code (Terraform) and deploying services to cloud platforms (GCP/AWS).
• Familiarity with CI/CD tooling and observability best practices (metrics, logs, tracing).
• Working knowledge of security best practices for data-sensitive systems and experience collaborating with Security & Compliance teams. Experience in healthcare or other regulated environments is strongly preferred.

Benefits

• Remote-first culture
• 401(k) savings plan through Fidelity
• Comprehensive medical, vision, and dental coverage through multiple medical plan options (including disability insurance)
• Paid Time Off ("PTO") and Discretionary Time Off (“DTO”)
• 12 weeks of 100% Paid Parental leave
• Family Building & Compassionate Leave: Fertility coverage, $25,000 for surrogacy/adoption, and paid leave for failed treatments, adoption or pregnancies.
• Work-From-Home reimbursement to support team collaboration home office work